Fluid-sensitive migration mechanisms predict association between metastasis and high interstitial fluid pressure in pancreatic cancer.

A remarkable feature in pancreatic cancer is the propensity to metastasize early, even for small, early stage cancers. We use a computer-based pancreatic model to simulate tumor progression behavior where fluid-sensitive migration mechanisms are accounted for as a plausible driver for metastasis. The model has been trained to comply with in vitro results to determine input parameters that characterize the migration mechanisms. To mimic previously studied preclinical xenografts we run the computer model informed with an ensemble of stochastic-generated realizations of unknown parameters related to tumor microenvironment only constrained such that pathological realistic values for interstitial fluid pressure (IFP) are obtained. The in silico model suggests the occurrence of a steady production of small clusters of cancer cells that detach from the primary tumor and form isolated islands and thereby creates a natural prerequisite for a strong invasion into the lymph nodes and venous system. The model predicts that this behavior is associated with high interstitial fluid pressure (IFP), consistent with published experimental findings. The continuum-based model is the first to explain published results for preclinical models which have reported associations between high IFP and high metastatic propensity and thereby serves to shed light on possible mechanisms behind the clinical aggressiveness of pancreatic cancer.

In silico investigations of intratumoral heterogeneous interstitial fluid pressure.

Recent preclinical studies have shown that interstitial fluid pressure (IFP) within tumors can be heterogeneous Andersen et al. (2019). In that study tumors of two xenograft models, respectively, HL-16 cervical carcinoma and Panc-1 pancreatic carcinoma, were investigated. Significant heterogeneity in IFP was reported and it was proposed that this was associated with division of tissue into compartments separated by thick connective tissue bands for the HL-16 tumors and with dense collagen-rich extracellular matrix for the Panc-1 tumors. The purpose of the current work is to explore these experimental observations by using in silico generated tumor models. We consider a mathematical multiphase model which accounts for tumor cells, fibroblasts and interstitial fluid. The model has been trained to comply with experimental in vitro results reported in Shieh et al. (2011) which has identified autologous chemotaxis, ECM remodeling, and cell-fibroblast interaction as drivers for invasive tumor cell behavior. The in silico model is informed with parameters that characterize the leaky intratumoral vascular network, the peritumoral lymphatics which collect the fluid, and the density of ECM as represented through the hydraulic conductivity of the interstitial space. Heterogeneous distribution of solid stress may result in heterogeneous compression of blood vessels and, thus, heterogeneous vascular density inside the tumor. To mimic this we expose the in silico tumor to an intratumoral vasculature whose net effect of density of blood vesssels and vessel wall conductivity is varied through a 2D Gaussian variogram constrained such that the resulting IFPs lie within the range as reported from the preclinical study. The in silico cervical carcinoma model illustrates that sparse ECM was associated with uniform intratumoral IFP in spite of heterogeneous microvascular network, whereas compartment structures resulted in more heterogeneous IFP. Similarly, the in silico pancreatic model shows that heterogeneity in the microvascular network combined with dense ECM structure prevents IFP to even out and gives rise to heterogeneous IFP. The computer model illustrates how a heterogeneous invasive front might form where groups of tumor cells detach from the primary tumor and form isolated islands, a behavior which is natural to associate with metastatic propensity. However, unlike experimental studies, the current version of the in silico model does not show an association between metastatic propensity and elevated IFP.

Collective tumor cell migration in the presence of fibroblasts.

In this work we investigate fibroblast-enhanced tumor cell migration in an idealized tumor setting through a computational model based on a multiphase approach consisting of three phases, namely tumor cells, fibroblasts and interstitial fluid. The interaction between fibroblasts and tumor cells has previously been investigated through this model (Urdal et al., 2019) to comply with reported in vitro experimental results (Shieh et al., 2011). Using the information gained from in vitro single-cell behavior, what will the effect of fibroblast-enhanced tumor cell migration be in a tumor setting? In particular, how will tumor cells migrate in a heterogeneous tumor environment compared to controlled in vitro microfluidic-based experiments? From what we know about the behavior of a tumor, is that collective invasion into adjacent tissue is frequently observed. Here, we want to elucidate how fibroblasts may guide tumor cells towards draining lymphatics to which tumor cells may subsequently intravasate and thus spread to other parts of the body. Fibroblasts can act as leader cells, where they create tracks within the extracellular matrix (ECM) by matrix remodeling and contraction. In addition, a heterotypic mechanical adhesion between fibroblasts and tumor cells also assist the fibroblasts to act as leader cells. Our simulation results show how the interaction between the two cell types yields collective migration of tumor cells outwards from the tumor where fibroblasts dictate the direction of migration. The model also describes how this well-orchestrated invasive behavior is the result of a proper combination of different interaction forces between cell-ECM, fibroblast-ECM, fluid-ECM and cell-fibroblast.

How Tumor Cells Can Make Use of Interstitial Fluid Flow in a Strategy for Metastasis.

INTRODUCTION: The phenomenon of lymph node metastasis has been known for a long time. However, the underlying mechanism by which malignant tumor cells are able to break loose from the primary tumor site remains unclear. In particular, two competing fluid sensitive migration mechanisms have been reported in the experimental literature: (i) autologous chemotaxis (Shields et al. in Cancer Cell 11:526-538, 2007) which gives rise to downstream migration; (ii) an integrin-mediated and strain-induced upstream mechanism (Polacheck et al. in PNAS 108:11115-11120, 2011). How can these two competing mechanisms be used as a means for metastatic behavior in a realistic tumor setting? Excessive fluid flow is typically produced from leaky intratumoral blood vessels and collected by lymphatics in the peritumoral region giving rise to a heterogeneous fluid velocity field and a corresponding heterogeneous cell migration behavior, quite different from the experimental setup. METHOD: In order to shed light on this issue there is a need for tools which allow one to extrapolate the observed single cell behavior in a homogeneous microfluidic environment to a more realistic, higher-dimensional tumor setting. Here we explore this issue by using a computational multiphase model. The model has been trained with data from the experimental results mentioned above which essentially reflect one-dimensional behavior. We extend the model to an envisioned idealized two-dimensional tumor setting. RESULT: A main observation from the simulation is that the autologous chemotaxis migration mechanism, which triggers tumor cells to go with the flow in the direction of lymphatics, becomes much more aggressive and effective as a means for metastasis in the presence of realistic IF flow. This is because the outwardly directed IF flow generates upstream cell migration that possibly empowers small clusters of tumor cells to break loose from the primary tumor periphery. Without this upstream stress-mediated migration, autologous chemotaxis is inclined to move cells at the rim of the tumor in a homogeneous and collective, but space-demanding style. In contrast, inclusion of realistic IF flow generates upstream migration that allows two different aspects to be synthesized: maintain the coherency and solidity of the the primary tumor and at the same time cleave the outgoing waves of tumor cells into small clusters at the front that can move collectively in a more specific direction.

Enhanced cancer cell invasion caused by fibroblasts when fluid flow is present.

It has been demonstrated that interstitial fluid (IF) flow can play a crucial role in tumor cell progression. Swartz and collaborators (Cancer Cell 11: 526-538, Shields et al. 2007) demonstrated that cells that secrete the lymphoid homing chemokines CCL21/CCL19 and express their receptor CCR7 could use flow to bias the secreted chemokine, causing pericellular gradients that stimulate cells to migrate in the direction of the flow. In a further work by Shieh et al. (Cancer Res 71: 790-800, 2011), a synergetic enhancement of tumor cell invasion caused by interaction between tumor cells and fibroblasts in the presence of fluid flow was reported. In the present work, we extend a previous proposed cell-fluid mathematical model for autologous chemotaxis (Chem Eng Sci 191: 268-287, Waldeland and Evje 2018) to also include fibroblasts. This results in a cell-fibroblast-fluid model. Motivated by the experimental findings by Shieh et al, the momentum balance equation for the fibroblasts involves (1) a stress term that accounts for chemotaxis in the direction of positive gradients in secreted growth factor TGF-[Formula: see text]; (2) a fibroblast-ECM interaction term; (3) a cancer cell-fibroblast interaction term. Imposing reasonable simplifying assumptions, we derive an explicit expression for the cancer cell velocity [Formula: see text] that reveals a balance between a fluid-generated stress term, a chemotactic-driven migration term (autologous chemotaxis), and a new term that accounts for the possible mechanical interaction between fibroblasts and cancer cells. Similarly, the model provides an expression for the fibroblast velocity [Formula: see text] as well as the IF velocity [Formula: see text]. The three-phase model is then used for comparison of the simulated output with experimental results to elucidate some of the possible mechanism(s) behind the reported fibroblast-enhanced tumor cell invasion.

Competing tumor cell migration mechanisms caused by interstitial fluid flow.

In the seminal work by Swartz and collaborators (Shields et al., 2007) it was discovered that autologously secreted or activated (ECM-bound) chemokine forms local pericellular diffusion gradients skewed by fluid convection, and the cells subsequently chemotact up the flow-directed gradient. However, in (Polacheck et al., 2011) Kamm and collaborators found that there is a competing downstream and upstream migration transport mechanism. Their study showed that both mechanisms are present at the same time and the relative strength of these two stimuli governs the directional bias in migration for a cell population and is a function of cell density, interstitial flow rate, and CCR7 receptor availability. The main objective of this work is to give a possible explanation of these two different concurrent cell migration mechanisms by means of a theoretical model. Relying on multiphase modelling, separate momentum balance equations are formulated, respectively, for the cell phase and the interstitial fluid (IF) phase. In order to represent proteolytic activity and autologous chemotaxis a non-moving ECM component is included, as well as proteases secreted by the cancer cells and chemokine that can be released from ECM. The cell and IF momentum balance equations include cell-ECM and fluid-ECM resistance force terms (i.e., classical Darcy's equation terms), but also a cell-fluid interaction term that can account for a more indirect effect that fluid-generated stress may have on cancer cells. We illustrate how the cancer cells can work through this term and effectively avoid being pushed in the flow direction, and even create upstream migration by controlling its magnitude and sign. We think of this as the mathematical interpretation of the experimental observation by Kamm and collaborators that the fluid generated matrix adhesion tension on the upstream side of cells activates integrin adhesion complexes, resulting in activation of focal adhesion (FA) proteins. The model predicts that generally the strength of the upstream migration mechanism is sensitive to the cell volume fraction: a lower density of cells is subject to a weaker upstream migration effect; a higher density of cancer cells can more effectively generate upstream migration. This behavior is a result of the nonlinear coupling between cell-ECM, fluid-ECM, and cell-fluid interaction terms that naturally are involved in the mathematical expression for the net cell velocity.